Weiß Frey Patrick (47 results)

300 Seiten, mit einer farbigen Abbildung, Original-Leinen. Erste Ausgabe. Eines von 2000 Exemplaren. Sauberes Exemplar ohne Stempel oder Anstreichungen. Sehr gut erhalten. Sprache: deu.

Condition: New.

Condition: As New. Unread book in perfect condition.

Condition: New.

Condition: New.

Paperback. Condition: New.

Condition: New. In.

Paperback. Condition: New. This textbook shows how to bring theoretical concepts from finance and econometrics to the data. Focusing on coding and data analysis with Python, we show how to conduct research in empirical finance from scratch. We start by introducing the concepts of tidy data and coding principles using pandas, numpy, and plotnine. Code is provided to prepare common open-source and proprietary financial data sources (CRSP, Compustat, Mergent FISD, TRACE) and organize them in a database. We reuse these data in all the subsequent chapters, which we keep as self-contained as possible. The empirical applications range from key concepts of empirical asset pricing (beta estimation, portfolio sorts, performance analysis, Fama-French factors) to modeling and machine learning applications (fixed effects estimation, clustering standard errors, difference-in-difference estimators, ridge regression, Lasso, Elastic net, random forests, neural networks) and portfolio optimization techniques.Key Features:Self-contained chapters on the most important applications and methodologies in finance, which can easily be used for the reader's research or as a reference for courses on empirical finance.Each chapter is reproducible in the sense that the reader can replicate every single figure, table, or number by simply copying and pasting the code we provide.A full-fledged introduction to machine learning with scikit-learn based on tidy principles to show how factor selection and option pricing can benefit from Machine Learning methods.We show how to retrieve and prepare the most important datasets financial economics: CRSP and Compustat, including detailed explanations of the most relevant data characteristics.Each chapter provides exercises based on established lectures and classes which are designed to help students to dig deeper. The exercises can be used for self-studying or as a source of inspiration for teaching exercises.

Condition: New. 1st edition NO-PA16APR2015-KAP.

Condition: As New. Unread book in perfect condition.

Paperback. Condition: New. This textbook shows how to bring theoretical concepts from finance and econometrics to the data. Focusing on coding and data analysis with Python, we show how to conduct research in empirical finance from scratch. We start by introducing the concepts of tidy data and coding principles using pandas, numpy, and plotnine. Code is provided to prepare common open-source and proprietary financial data sources (CRSP, Compustat, Mergent FISD, TRACE) and organize them in a database. We reuse these data in all the subsequent chapters, which we keep as self-contained as possible. The empirical applications range from key concepts of empirical asset pricing (beta estimation, portfolio sorts, performance analysis, Fama-French factors) to modeling and machine learning applications (fixed effects estimation, clustering standard errors, difference-in-difference estimators, ridge regression, Lasso, Elastic net, random forests, neural networks) and portfolio optimization techniques.Key Features:Self-contained chapters on the most important applications and methodologies in finance, which can easily be used for the reader's research or as a reference for courses on empirical finance.Each chapter is reproducible in the sense that the reader can replicate every single figure, table, or number by simply copying and pasting the code we provide.A full-fledged introduction to machine learning with scikit-learn based on tidy principles to show how factor selection and option pricing can benefit from Machine Learning methods.We show how to retrieve and prepare the most important datasets financial economics: CRSP and Compustat, including detailed explanations of the most relevant data characteristics.Each chapter provides exercises based on established lectures and classes which are designed to help students to dig deeper. The exercises can be used for self-studying or as a source of inspiration for teaching exercises.

Paperback. Condition: Brand New. 272 pages. 10.00x7.00x10.00 inches. In Stock.

Condition: New. Christoph Frey is a Quantitative Researcher and Portfolio Manager at a family office in Hamburg and a Research Fellow at the Centre for Financial Econometrics, Asset Markets and Macroeconomic Policy at Lancaster University. Prior to this, he was t.

Paperback. Condition: New. This textbook shows how to bring theoretical concepts from finance and econometrics to the data. Focusing on coding and data analysis with Python, we show how to conduct research in empirical finance from scratch. We start by introducing the concepts of tidy data and coding principles using pandas, numpy, and plotnine. Code is provided to prepare common open-source and proprietary financial data sources (CRSP, Compustat, Mergent FISD, TRACE) and organize them in a database. We reuse these data in all the subsequent chapters, which we keep as self-contained as possible. The empirical applications range from key concepts of empirical asset pricing (beta estimation, portfolio sorts, performance analysis, Fama-French factors) to modeling and machine learning applications (fixed effects estimation, clustering standard errors, difference-in-difference estimators, ridge regression, Lasso, Elastic net, random forests, neural networks) and portfolio optimization techniques.Key Features:Self-contained chapters on the most important applications and methodologies in finance, which can easily be used for the reader's research or as a reference for courses on empirical finance.Each chapter is reproducible in the sense that the reader can replicate every single figure, table, or number by simply copying and pasting the code we provide.A full-fledged introduction to machine learning with scikit-learn based on tidy principles to show how factor selection and option pricing can benefit from Machine Learning methods.We show how to retrieve and prepare the most important datasets financial economics: CRSP and Compustat, including detailed explanations of the most relevant data characteristics.Each chapter provides exercises based on established lectures and classes which are designed to help students to dig deeper. The exercises can be used for self-studying or as a source of inspiration for teaching exercises.

Paperback. Condition: New. This textbook shows how to bring theoretical concepts from finance and econometrics to the data. Focusing on coding and data analysis with Python, we show how to conduct research in empirical finance from scratch. We start by introducing the concepts of tidy data and coding principles using pandas, numpy, and plotnine. Code is provided to prepare common open-source and proprietary financial data sources (CRSP, Compustat, Mergent FISD, TRACE) and organize them in a database. We reuse these data in all the subsequent chapters, which we keep as self-contained as possible. The empirical applications range from key concepts of empirical asset pricing (beta estimation, portfolio sorts, performance analysis, Fama-French factors) to modeling and machine learning applications (fixed effects estimation, clustering standard errors, difference-in-difference estimators, ridge regression, Lasso, Elastic net, random forests, neural networks) and portfolio optimization techniques.Key Features:Self-contained chapters on the most important applications and methodologies in finance, which can easily be used for the reader's research or as a reference for courses on empirical finance.Each chapter is reproducible in the sense that the reader can replicate every single figure, table, or number by simply copying and pasting the code we provide.A full-fledged introduction to machine learning with scikit-learn based on tidy principles to show how factor selection and option pricing can benefit from Machine Learning methods.We show how to retrieve and prepare the most important datasets financial economics: CRSP and Compustat, including detailed explanations of the most relevant data characteristics.Each chapter provides exercises based on established lectures and classes which are designed to help students to dig deeper. The exercises can be used for self-studying or as a source of inspiration for teaching exercises.

Condition: As New. Unread book in perfect condition.

Condition: As New. Unread book in perfect condition.

Condition: New.

Condition: New.

Condition: New.

Condition: New. 1st edition NO-PA16APR2015-KAP.

Condition: New. In.

Hardcover. Condition: Brand New. 272 pages. 10.00x7.00x10.00 inches. In Stock.

18,5:11,2 cm. 1 Farbtafel. 300 S. OLn. Enthält Texte von Bice Curiger, Patrick Frey, Walter Keller, Caesar Menz, Robet Richter, Christoph Egger u.v.a.m. VERSAND ERFOLGT NUR MIT SENDUNGSNACHWEIS. SHIPMENT ONLY WITH TRACKING NUMBER!

Soft cover. Condition: As New. 1st Edition. Zürich: Parkett Verlag, 1988. (10 x 8 1/4 in., 25.4 x21 cm). 216pp. First edition. Illustrated wrappers as new in publisher's shrinkwrap. Text in German and English. 12pp. insert by Louise Bourgeois. Collaboration Peter Fischli and David Weiss essays: Friendship is Unstable Equilibrium (On the Beginnings of a Model Collaboration) by Patrick Frey; Fischli / Weiss In Appearance by Germano Celant; The Path of Most Resistance by Karen Marta; Peter Fischli and David Weiss by Bernhard Johannes Blume; The Critic as Four-Eyed Peg Leg by Jeanne Silverthorne; (Dis)ordered Artifice in the Art of Fischli/Weiss by Sidra Stich. Profusely illustrated. A terrific overview of the artists' work to date.

Couverture rigide. Condition: Très bon. Sm.8° - 300pp - One color reproductions (frontispice). Peter Fischli (1952) & David Weiss (1946-2012) Fischli/Weiss Swiss artist duo! First edition, text in German language.

Hardcover. Condition: As New. 1st Edition. Sm.8° - 300pp - One color reproductions (frontispice). Peter Fischli (1952) & David Weiss (1946-2012) Fischli/Weiss Swiss artist duo! First edition, text in German language. Original boards. As New!

Hardcover. Condition: Sehr gut. 1. Auflage. Z/W : 352 Seiten, 17 x 22 cm, 182 farbige und s/w Abbildungen - Dieses einzigartige Buch, das in Zusammenarbeit mit den Künstlern entwickelt wurde, begleitet eine große, retrospektive Wanderausstellung und ist die umfangreichste visuelle Aufzeichnung ihres außergewöhnlich vielfältigen Werks, das bisher veröffentlicht wurde. Zu den vorgestellten Autoren gehören Kritiker, Kuratoren, Kulturkommentatoren, Künstler und Filmemacher, die eine Vielzahl von Stimmen in eine Karriere einbringen, die sich ebenso leicht über Grenzen hinwegsetzt wie sich einer einfachen Klassifizierung entzieht.

Softcover, staple-bound, 12 pages; in English, German and Italian; good condition; moderate scuffs and rubbing to covers; mostly on rear; light ot moderate edgewear with a few creases to pages at upper left corner; no internal marks. A catalog of the rubber works.

First Edition. First edition. Softcover. Exhibition catalog for a show that ran September through October 1988. Text in German with contributions by Patrick Frey and Bice Curiger. Includes with the covers 22 black and white illustrations, a black and white photograph of the artists, brief artist biographies, list of previous exhibitions, and bibliography. A near fine copy in wrappers that are very lightly soiled and with some very minute wear. A nice copy of this uncommon catalog.